The scope of machinima has led to a very wide spectrum of usage, summarised in figure 1. In classifying machinima, which now encompasses such a diverse body of work that can be seen over many distribution networks well beyond YouTube, we have developed a matrix using the extent of interaction in the production process and the commercialization of the content arising from it.

The sandbox (or free-roam) nature of such games (in which game rules are fewer and more flexible) allows for greater experimentation, allowing the development story lines and narratives unassociated with the core themes / objectives of the game. As familiarity with the game world is no longer a prerequisite, a much wider audience is potentially available and this is reflected in the channels of distribution, which extend beyond the communities of their ‘parent’ worlds, leading to forms of machinima that can be described as ‘experimental’ and ‘political’.

Machinima distributed through these channels is intended to entertain, stimulate and provoke audiences but their direct involvement and / or interaction is not a requirement. To this end, material found here has more in common with gallery-based digital art, film and even TV - namely cinematic and video-based works, to be viewed passively. The primary outlets and hubs are currently the video sharing networks YoutubeTM and VimeoTM, supported by various umbrella sites which form ‘embedded’ collections or galleries of works stored on their servers (e.g. Machinima.com, Twitch). In either case compressed, rendered frames are uploaded and can be and shared either privately or publicly by community members. It should be noted, however, that restrictions on upload may be imposed by the channel owner in order to comply with copyright / ownership / decency laws. As such, machinima works distributed via popular channels in this quadrant are subject to indiscriminate censorship (Cornblatt, 2011).

Recognized social networks such as Facebook(TM) and Twitter(TM) also contribute to these channels - with the ability to ‘like’, ‘share’ and ‘retweet’ posts providing opportunities to achieve further reach, their main use is to stimulate interest in and drive critical discussion with viewers. In rare cases, mainstream media will also drive viewers to such channels (e.g. Comedy Central’s South Park episode ‘Make Love Not Warcraft’ and UK Channel 4’s series ‘SuperMes’).

The extended possibilities of individual social media platforms to monetize viewing audiences (through overlaid advertising) may further support the development of commercial distribution networks for machinimators. These depend upon the extent of producers’ personal social networks and their ability to market their products. Where most successful, viewers are encouraged to become subscribers to personal channels created as sub-sets of the social media platform albeit the machinimator may generate little direct value beyond the miniscule revenue generated from overlaid advertising (based on numbers of viewers).

V-learning (‘leaky-walled’) channels do not provide works intended for general or recreational viewing. Entry to these channels is granted by invitation, registration or, in the case of monetized models, through subscription. It also differs from Walled Channels as machinima is not considered to be confidential or restricted. The ‘opt-in’ framework is similar to those found amongst the Gaming Channels, although here the subject matter and themes are unrelated to game-play or gaming culture. Instead, it is suggested that all machinima distributed in this quadrant will in some way lend itself to the dissemination of new knowledge and ideas, either as part of a formal, directed learning programme (e.g. MOOC) or through scenarios based around interactive play or simulation (e.g. Serious Games). We therefore describe this quadrant as virtual-learning, or v-learning channels. We do not see this as the same e-learning, which is internet enabled, because it uses a game context to add depth and richness to the learning environment through enhanced and immersive performance-based experiences. Machinima here will not be completely hidden from general audiences and permission will be granted for selected works (or excerpts) to be viewed outside of the channels. This ‘leaky walled’ model enables examples and introductory material to be appear in domains where the potential audience (e.g. new v-learners) may reside.